Obrazec predmeta (pdf)

UČNI NAČRT PREDMETA / COURSE SYLLABUS 2014/2015
Statistika
Statistics
Predmet:
Course Title:
Študijski program
Study programme
UNI-Ekonomske in poslovne vede
UNI-Economic and business
sciences
Študijska smer
Study field
Letnik
Year
Semester
Semester
vse
2.
3.
Obvezni
Vrsta predmeta/ Course type:
Univerzitetna koda predmeta / University subject code:
Predavanja
Lectures
Seminar
Seminar
Sem. vaje
Tutorial
45
15
Nosilec predmeta / Lecturer:
Jeziki: S/A
Languages: S/E
Lab. vaje
Labor
work
15
Teren. vaje
Field work
Samost. delo
Individ.
work
75
ECTS
5
Kavkler A. – 1.del (the first part) ,Tominc P. – 2.del (the second
part)
Predavanja /
Lecture:
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za
opravljanje študijskih obveznosti:
Prerequisits:
Vsebina:
Vsebina 1. dela predmeta:
Osnove verjetnostnega računa: poskusi in
dogodki, operacije z dogodki, statistična in
klasična definicija verjetnosti, verjetnost
produkta, Bernoullijeva formula.
Empirične porazdelitve: frekvenčne
porazdelitve, aritmetična sredina, vzorčna
varianca, vzorčni momenti.
Diskretne in zvezne porazdelitve: definicija
in osnovni pojmi, porazdelitvena funkcija,
matematično upanje, varianca, momenti,
pomembnejše porazdelitve (binomska,
Poissonova, hipergeometrijska, normalna,
 2 - porazdelitev, t – porazdelitev, F –
porazdelitev).
Osnove vzorčenja in testiranje statističnih
domnev: končna in neskončna statistična
mnoţica, cenilke in ocene parametrov,
intervalsko ocenjevanje parametrov, napake
1. in 2. vrste,  2 - test, u – test, t – test, F –
Content (Syllabus outline):
Content of the first part
Probability theory basics: trials and events, event
operations, statstical and classical definition of
probability, product probability, Bernoulli formula.
Empirical distributions: frequency distributions,
arithmetic mean, sample variance, sample
moments.
Discrete and continuous distributions: definition
and basic notions, distribution function, mean,
variance, moments, important distributions
(binomial, Poisson, hypergeometric, normal,  2 distribution, t – distribution and F – distribution).
Sampling and hypothesis testing: finite and infinite
statistical set, statistics and parameter estimation,
interval parameter estimates, type I error and type
II error,  2 - test, u – test, t – test, F – test.
Statistical software: SPSS.
Economic applications are included in most
chapters.
test.
Uporaba statistične programske opreme:
SPSS.
Vsebina 2. dela predmeta:
zbiranje podatkov
prikazovanje podatkov v tabelah in grafih
relativna števila (indeksi)
Srednje vrednosti, mere variabilnosti,
asimetrije in sploščenosti
Intervalno ocenjevanje vrednosti statističnih
parametrov in osnove preizkušanja domnev o
statističnih parametrih
Osnove enostavne regresije
Osnove analize in napovedovanja vrednosti v
časovnih vrstah.
Uporaba SPSS in Excella
Content of the second part:
Data-collection
Graphs and table constructions
Relative numbers (indices)
Measures of central tendency, measures of
dispersion, skewness and curtosis
Estimation and basics of hypothesis testing
Basics of simple regression
Basics of the time series analysis and forecasting
Use of software package (SPSS) and the use of
Excel.
Temeljni literatura in viri / Textbooks:
del predmeta - The first part:
S. Indihar, I. Kavkler, M. Mastinšek, Matematika za ekonomiste, 1. del, EPF, Maribor, 2002.
A. Kavkler, I. Kavkler. Zapiski predavanj pri predmetu Statistika, 1. del. EPF, 2014.
A. Kavkler. Gradivo za vaje pri predmetu Statistika, 1. del. EPF, 2014.
J. Marovt, Statistika (1. del predmeta), Učno gradivo pri predmetu Statistika (1. del predmeta), interno
gradivo, EPF, 2008.
G. Keller, B. Warrack, Statistics for Management and Economics, Thomson Learning, London, 2000.
J. Marovt, Gradivo pri predmetu Statistika: praktikum iz osnov verjetnostnega računa, EPF, Maribor, 2010
del predmeta – The second part
Tominc Polona: Statistika (2. del predmeta), Učno gradivo pri predmetu Statistika (2. del predmeta),
interno gradivo, EPF, 2007/2008
Izbrana poglavja iz (Selected chapters)
Groebner, Shannon, Fry, Smith: Business statistics – a decision-making approach, Pearson Prentice
Hall, 2001, 2005.
Cilji in kompetence:
Študenti:
1. Spoznajo uporabnost statističnih metod pri
reševanju poslovnih problemov.
2. Utrdijo in nadgradijo teoretično znanje na
področju statističnih tehnik in metod, ki
omogočajo spremeniti različne podatke v
uporabne
informacije
za
poslovno
odločanje.
3. Osvojijo analitičen matematično statističen
pristop k preučevanju poslovnih problemov,
ki se sestoji iz korakov:
- formulacija problema na statističen
način
- izbira ustrezne statistične metode
- reševanje problema
- interpretacija rezultatov v smislu
moţnih rešitev problema.
Predvideni študijski rezultati:
Objectives:
Students:
1. Are familiarised with the applicability of statistical
methods for business problems.
2. Enhance their theoretical knowledge in the field of
of statistical techniques and methods with the
purpose to be able to develop different data into
useful information for business decision making.
3. Acquire
analytical
mathematical-statistical
approach to analysis of business problems,
consisting of:
- Formulate the problem in terms of statistics.
- Identify the appropriate statistical techniques.
- Solve the problem.
- Interpret the results (what the solution means for
the problem at hand).
Intended learning outcomes:
Znanje in razumevanje:
Študenti:
1. Osvojijo osnovne pojme deskriptivne in
matematične statistike.
2. Se naučijo uporabljati statistične metode
pri reševanju poslovnih problemov.
3. Se zavedajo etičnih vprašanj na
področju statistične analize.
4. Etična vprašanja znajo uskladiti z
lastnimi pogledi.
Development of knowledge and understanding:
Students:
1. Understand basic concepts of .descriptive and
mathematical statistics.
2. Learn to apply statistical methods in solving
business problems.
3. Can demonstrate awareness of ethical issues in
the field of statistical analysis.
4. Are able to discuss ethical issues in relation to
personal beliefs and values.
Kognitivne/Intelektualne veščine
Študenti:
1. Ob upoštevanju navodil znajo izvesti
osnovno analizo, upoštevajoč določena
izhodišča.
2. Znajo zbrati in urediti podatke in ideje
na standarden način.
3. Znajo presoditi o zanesljivosti podatkov
na osnovi znanih metod in po navodilih.
4. Študenti se oblikujejo kot samostojno
misleči in v reševanje problemov
usmerjeni ljudje.
Cognitive/Intellectual skills:
Students:
1. Can analyse with guidance using given
classification/principles.
2. Can collect and arrange data and ideas in a
standard way.
3. Can evaluate the reliability of data using
defined techniques and under guidance.
4. Students develop greater independence of
thought and the ability to solve problems.
Ključne/prenosljive veščine in spretnosti
Študenti:
1. Uporabljajo IKT.
2. Razvijajo spretnosti za timsko delo.
3. Izgrajujejo profesionalno etiko.
4. Razvijajo študijske tehnike in strategije
za samoizobraţevanje, stalno refleksijo
in evalvacijo.
5. Razvijajo interes za vseţivljenjsko
učenje.
Key/Transferable skills
Students:
1. Use ICT.
2. Develop skills for team work.
3. Develop professional ethics.
4. Develop learning techniques and strategies for
individual study, permanent reflection and
evaluation.
5. Develop interest for lifelong learning.
Metode poučevanja in učenja:
Learning and teaching methods:
predavanja;
lectures;
AV predstavitve;
AV presentations;
obravnava študijskih primerov;
case studies;
aktivno individulano in skupinsko delo
active individual and group work
Delež (v %) /
Načini ocenjevanja:
Weight (in %):
Assessment:
- aktivno delo na predavanjih in 20%
-active participation in class discussions;
vajah;
- pisni izpit
80%
-seminar research work;
Študent lahko pisni izpit
-written examination or 2 tests
nadomesti z dvema vmesnima
testoma
The exam is passed when 44 out of 80
Študent opravi izpit, če na
points are obtained by written axam AND
pisnem delu (ali na obeh testih
at the same time, the sum together with
skupaj) zbere najmanj 44 točk
points obtained by the active participation
od 80-ih moţnih, hkrati pa
in class, equals at least 56 points (out of
skupaj s točkami aktivnega dela
all 100).
zbere najmanj 56 točk (od
skupnih 100 točk).
Reference nosilca / Lecturer's references:
KAVKLER, Alenka, FESTIĆ, Mejra. Smooth transition regression model for Slovene stock exchange index
returns. Econ. Comput. Econ. Cybern. Stud. Res., 2010, vol. 44, no. 1, str. 147-164.
KAVKLER, Alenka, DANACICA, Daniela-Emanuela, BABUCEA, Ana Gabriela, BIĆANIĆ, Ivo, BÖHM,
Bernhard, TEVDOVSKI, Dragan, TOŠEVSKA, Katerina, BORŠIČ, Darja. Cox regression models for
unemployment duration in Romania, Austria, Slovenia, Croatia, and Macedonia. Rom. J. Econ. Forecast., 2009,
2, str. 81-104.
DAJČMAN, Silvo, KAVKLER, Alenka. A comparative DCC-GARCH and rolling wavelet correlation analysis
of interdependence between the Slovenian and European stock markets. Econ. Comput. Econ. Cybern. Stud.
Res., 2011, vol. 45, no. 4, str. 99-118.
FESTIĆ, Mejra, KAVKLER, Alenka. The roots of the banking crisis in the new EU member states : a panel
regression approach. Rom. J. Econ. Forecast., 2012, vol. 15, iss. 1, str. 20-40.
KAVKLER, Alenka, BORŠIČ, Darja, BEKŐ, Jani. PPP in Central and Eastern European economies : further
evidence from panel unite root tests. Appl. econ. lett. (Print), 2012, vol. 19, iss. 16, str. 1543-1548, doi:
10.1080/13504851.2011.637891.
FESTIĆ, Mejra, REPINA, Sebastijan, KAVKLER, Alenka. The dynamics of energy price movements estimating
coal price dynamics with the principal component method = Dinamika gibanja cen energentov in ocena
dinamike gibanja cen premoga z metodo glavnih komponent. Journal of energy technology, 2009, vol. 2, iss. 2,
str. 19-40.
DAJČMAN, Silvo, FESTIĆ, Mejra, KAVKLER, Alenka. Multiscale test of CAPM for three Central and Eastern
European stock markets. Journal of business economics and management, 2013, vol. 14, no. 1, str. 54-76.
RADONJIČ, Gregor, TOMINC, Polona. Pomen sistema ravnanja z okoljem ISO 14001 za tehnološko
posodabljanje proizvodnih podjetij = The role of the environmental management standard ISO 14001
in technological improvements in manufacturing companies. Naše gospod., 2007, letn. 53, št. 3/4, str.
58-70. [COBISS.SI-ID 9156892]
TOMINC, Polona, REBERNIK, Miroslav. Growth aspirations and cultural support for
entrepreneurship : a comparison of post-socialist countries. Small bus. econ., 2007, vol. 28, no. 2/3,
str. [239]-255. [COBISS.SI-ID 9039388]
DUH, Mojca, TOMINC, Polona, REBERNIK, Miroslav. The importance of family enterprises in
transition economies : Is it overestimated?. East. Europ. econ., 2009, vol. 47, no. 6, str. 22-42, tabele.
[COBISS.SI-ID 10101788]
TOMINC, Polona, REBERNIK, Miroslav. Connections of entrepreneurial capacity and openness
towards innovations with the individual's decision to become an entrepreneur : a case from Slovenia.
Soc. econ. (Print), 2010, vol. 32, no. 2, str. [297]-313, doi: 10.1556/SocEc.2010.0002. [COBISS.SI-ID
10519068]
MAKOVŠEK, Dejan, TOMINC, Polona, LOGOŢAR, Klavdij. A cost performance analysis of
transport infrastructure construction in Slovenia. Transportation (Dordr.), Online FirstT, 29 January
2011, doi: 10.1007/s11116-011-9319-z. [COBISS.SI-ID 10564892]